Spotlight

What if AI didn’t just assist with data but digitized the physical world’s most critical aging infrastructure?

Quick Pitch: ConeLabs is an AI powered infrastructure inspection platform that converts drone imagery into inspection grade 3D models, enabling faster, safer, and standardized bridge assessments.

The Problem

• Manual workflows: Over 600,000 bridges in the U.S. require recurring inspections, yet many reviews remain labor intensive and paper based.

• Safety exposure: Inspectors enter hazardous environments and often require lane closures to collect data.

• Inconsistent records: Manual interpretation limits standardization and long term condition tracking.

• Labor shortages: A shrinking pool of licensed inspectors leaves critical assets under reviewed.

Snapshot

• Industry: AI powered infrastructure inspection

• Headquarters: Waterloo, Ontario, Canada

• Year Founded: 2023

• Traction: Dozens of completed projects, growing customer base, proprietary training dataset exceeding one million images, and six figure ARR

Founder Profiles

• Albert Mansour, Co-Founder, CEO: Licensed civil engineer (Waterloo), former President of a global 3D modeling company, previously co-founded a fintech.

• Ahmed Mahmoud, Co-Founder, CTO: PhD in AI and sensor fusion, 12+ years in computer vision research, led government funded projects.

Funding

• Current Round: Raising $1.5M (Pre-Seed)

• Lead Investor: Techstars

Revenue Engine

• Hybrid model: SaaS subscriptions plus per project usage fees

• Project economics: Large bridge inspections can generate up to $100k per project

• Margin profile: Targeting 70%+ SaaS gross margins as they transition toward a full SaaS model in 2026

What Users Love

• Inspection grade 3D models from drone imagery

• In platform annotation, measurement, and AI defect detection

• Standardized reports aligned with DOT requirements

• Reduced field time and labor hours

Playing Field

• gNext Labs: Outsourced reconstruction with limited AI

• Trendspek: Outsourced reconstruction, no AI layer

• Aren: Relies on third party reconstruction and viewers

• Qii.ai: 2D workflows without 3D annotation

• T2D2: 2D defect detection only

Why It Matters

Infrastructure is aging while inspection remains largely manual and compliance driven. Bridge inspection alone represents a multibillion dollar market, with adjacent expansion into roads, runways, façades, and utilities. Digitization enables safer workflows, standardized records, and scalable asset oversight.

What Sets Them Apart

• Proprietary workflow: In house 3D reconstruction, purpose built viewer, and AI defect detection

• Data moat: 1.7M+ proprietary training images improving accuracy and defect coverage

• Regulatory alignment: Inspection grade outputs aligned with DOT standards

• Experienced team: Deep civil engineering and AI expertise

Analysis

Bulls Case 📈 

• Technically defensible end to end workflow

• Large, regulation driven market with recurring demand

• Early paying customers and compounding data advantage

• Founders with domain and technical credibility

Bears Case 📉 

• Long public sector sales cycles

• Need to convert pilots into durable SaaS contracts

• Expansion beyond bridges requires additional data and product adaptation

• GTM execution risk at scale

Verdict

ConeLabs sits at the intersection of aging infrastructure and AI driven digitization. The opportunity is not just modernization but ownership of the inspection data layer in a recurring, compliance driven market. If pilots convert into durable SaaS contracts and the data moat compounds, ConeLabs can evolve from a project tool into the system of record for asset condition management. Early stage, revenue generating, and positioned in a technically defensible niche

The Startup Pulse

Another happening week in startup funding. Strong activity across AI foundation models, data infrastructure, robotics, fusion energy, healthcare AI, and enterprise cybersecurity.

• Anthropic — Raised $30B Series G at a $380B valuation led by GIC and Coatue to expand frontier model development and global infrastructure.

• Databricks — Closed roughly $5B in financing to accelerate its unified data and AI platform and deepen enterprise adoption.

• Apptronik — Secured $520M to scale commercial deployment of its Apollo humanoid robot across logistics, manufacturing, and industrial automation.

Read more

Written by Ashher

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